9781451190052

Modern Epidemiology

  • ISBN 13:

    9781451190052

  • ISBN 10:

    1451190050

  • Edition: 3rd
  • Format: Hardcover
  • Copyright: 12/17/2012
  • Publisher: LWW

Note: Not guaranteed to come with supplemental materials (access cards, study guides, lab manuals, CDs, etc.)

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Summary

The thoroughly revised and updated Third Edition of the acclaimed Modern Epidemiology reflects both the conceptual development of this evolving science and the increasingly focal role that epidemiology plays in dealing with public health and medical problems. Coauthored by three leading epidemiologists, with contributions from sixteen experts in a variety of epidemiologic sub-disciplines, this new edition is by far the most comprehensive and cohesive text on the principles and methods of epidemiologic research.

The book covers a broad range of concepts and methods, including epidemiologic measures of occurrence and effect, study designs, validity, precision, statistical interference, and causal diagrams. Topics in data analysis range from Bayesian analysis, sensitivity analysis, and bias analysis, with an extensive overview of modern regression methods including logistic and survival regression, splines, hierarchical (multilevel) regression, propsensity scores and other scoring methods, and g-estimation. Special-topics chapters cover disease surveillance, ecologic studies, social epidemiology, infectious disease epidemiology, genetic and molecular epidemiology, nutritional epidemiology, environmental epidemiology, reproductive epidemiology, clinical epidemiology, and meta-analysis.

FEATURES:

  • Comprehensive and cohesive text on the principles and methods of contemporary epidemiologic research
  • Addresses the methodologic issues crucial to the wide range of epidemiologic applications in public health and medicine
  • Major sections cover basic concepts, study design and conduct, data analysis, and special topics
  • Completely revised and updated to bring you the most updated information
  • New chapters cover causal modeling: Bayesian analysis, probabilistic bias analysis, social epidemiology, and use of secondary data
  • Includes online access to full text so you have access to the content anytime

(Errata, July 2014)

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